Design of an Edge-Detection CMOS Image Sensor with Built-in Mask Circuits.
Minhyun JinHyeonseob NohMinkyu SongSoo Youn KimPublished in: Sensors (Basel, Switzerland) (2020)
In this paper, we propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that has built-in mask circuits to selectively capture either edge-detection images or normal 8-bit images for low-power computer vision applications. To detect the edges of images in the CIS, neighboring column data are compared in in-column memories after column-parallel analog-to-digital conversion with the proposed mask. The proposed built-in mask circuits are implemented in the CIS without a complex image signal processer to obtain edge images with high speed and low power consumption. According to the measurement results, edge images were successfully obtained with a maximum frame rate of 60 fps. A prototype sensor with 1920 × 1440 resolution was fabricated with a 90-nm 1-poly 5-metal CIS process. The area of the 4-shared 4T-active pixel sensor was 1.4 × 1.4 µm2, and the chip size was 5.15 × 5.15 mm2. The total power consumption was 9.4 mW at 60 fps with supply voltages of 3.3 V (analog), 2.8 V (pixel), and 1.2 V (digital).
Keyphrases
- deep learning
- convolutional neural network
- high speed
- artificial intelligence
- optical coherence tomography
- machine learning
- positive airway pressure
- liquid chromatography
- loop mediated isothermal amplification
- atomic force microscopy
- photodynamic therapy
- obstructive sleep apnea
- single molecule
- label free
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- electronic health record
- high resolution
- mass spectrometry
- solid phase extraction
- single cell
- light emitting
- sleep apnea